Supervised by Dr. Ye Zhao. Develop learning and control pipelines for dexterous clinical robotic manipulation, including high-precision pipetting.
Supervised by Dr. Lu Mi. Investigated Dale’s principle as an inductive bias for recurrent networks, with experiments in multi-task learning, continual learning, and reinforcement learning.
First-author paper accepted to NeurIPS 2026.
Supervised by Dr. Anqi Wu. Developed a framework to discover reusable motor motifs and recover reward structure from behavioral trajectories. Applied expectation–maximization to multi-reward MDPs to infer latent behavioral intentions.
First-author work on reusable motor motifs accepted to NeurIPS 2026; co-authored ICML 2025 work on switching, history-dependent rewards.